Shear wave trajectory detection in ultra-fast M-mode images for liver fibrosis assessment: A deep learning-based line detection approach.

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Bibliographic Details
Title: Shear wave trajectory detection in ultra-fast M-mode images for liver fibrosis assessment: A deep learning-based line detection approach.
Authors: Wang X; Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region., Liu B; Department of Computing, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region., Wu C; Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region., Huang Z; Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region., Zhou Y; School of Biomedical Engineering, University of Shenzhen, Shenzhen, China., Wu X; Department of Computing, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region., Zheng Y; Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region; Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region. Electronic address: ypzheng@ieee.org.
Source: Ultrasonics [Ultrasonics] 2024 Aug; Vol. 142, pp. 107358. Date of Electronic Publication: 2024 Jun 10.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 0050452 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1874-9968 (Electronic) Linking ISSN: 0041624X NLM ISO Abbreviation: Ultrasonics Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1874-9968
DOI:10.1016/j.ultras.2024.107358